Triple
T7829930
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manchester Arena Inquiry |
E181339
|
entity |
| Predicate | consideredInjuries |
P25887
|
FINISHED |
| Object | hundreds of injured people |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: hundreds of injured people | Statement: [Manchester Arena Inquiry, consideredInjuries, hundreds of injured people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: consideredInjuries Context triple: [Manchester Arena Inquiry, consideredInjuries, hundreds of injured people]
-
A.
injuriesApprox
chosen
Indicates an approximate or estimated number or extent of injuries associated with an event or entity.
-
B.
causeOfInjury
Indicates that one entity is the source or reason that another entity sustained an injury.
-
C.
allegedInjury
Indicates that an injury is claimed or asserted to have occurred, typically without being legally or factually established.
-
D.
hasInjuries
Indicates that an entity has sustained one or more physical or bodily injuries.
-
E.
injuryType
Indicates the specific kind or category of injury associated with an entity or event.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca8282ccec819083c48efb72d21cf9 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb04ac013c81909533fa348776f50c |
completed | March 30, 2026, 11:18 p.m. |
| PD | Predicate disambiguation | batch_69cae91ae008819098e56bbe51143b31 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:44 p.m.